Role of topology in the spontaneous cortical activity

Scarpetta et al. BMC Neuroscience 2015, 16(Suppl 1):P6 http://www.biomedcentral.com/1471-2202/16/S1/P

Cortical Phase Transitions as an Effect of Topology of Neural Network

Understanding the emerging of cortical dynamical state, its functional role, and its relationship with network topology, is one of the most interesting open questions in computational neuroscience. Spontaneous cortical dynamics often shows spontaneous fluctuations with UP/DOWN alternations and critical avalanches which resemble the critical fluctuations of a system posed near a non-equilibrium noise-induced phase transition. A model with structured connectivity and dynamical attractors has been shown to sustain two different dynamic states and a phase transition with critical behaviour is observed. We investigate here which are the features of the connectivity which permit the emergence of the phase transition and the large fluctuations near the critical line. We start from the original connectivity, that comes from the learning of the spatiotemporal patterns, and we shuffle the presynaptic units, leaving unchanged both the postsynaptic units and the value of the connections. The original structured network has a large clustering coefficient, since it has more directed connections which cooperate to activate a precise order of neurons, respect to randomized network. When we shuffle the connections we reduce the clustering coefficient and we destroy the spatiotemporal pattern attractors. We observe that the phase transition is gradually destroyed when we increase the ratio of shuffled connections, and already at a shuffling ratio of 70% both the phase transition and its critical features disappear

Structured Versus Shuffled Connectivity in Cortical Dynamics

Abstract Previous papers have studied a leaky Integrate-and-Fire (IF) model whose connectivity was designed in such a manner as to favor the spontaneous emergence of collective oscillatory spatiotemporal patterns of spikes. In this model the alternation of up and down states does not depend on a kind of neuron bistability, nor on synaptic depression, but is rather a network effect. In order to check if the transition region with bimodal distribution of the firing rate survive even after changes in the topology of the network, in this work we shuffle all the connections. For each chosen connection we change the presynaptic neuron, choosing as the new presynaptic one a random neuron of the network. After shuffling the connections, not only the number of excitatory and inhibitory connections is the same as before, but also the strengths of the connections are the same, and only the topology is changed. We observe that shuffling the connections changes the features of the dynamics dramatically. Before shuffling the system has a transition from a regime of Poissonian noisy activity to a regime of spontaneous persistent collective replay, and at the transition point the network dynamics shows an intermittent reactivation of the stored patterns, with alternation of up and down state, and bimodal distribution of spiking rate. Shuffling all the connections we observe that the transition region with bimodal distribution disappears, and the dynamics is Poissonian with unimodal rate distribution for all the investigated parameters. These results show the role of topology in dictating the emerging collective dynamics of neural circuits

Hysteresis, neural avalanches and critical behaviour near a rst-order transition of a spiking neural network

Many experimental results, both in-vivo and in-vitro, support the idea that the brain cortex operates near a critical point, and at the same time works as a reservoir of precise spatio-temporal patterns. However the mechanism at the basis of these observations is still not clear. In this paper we introduce a model which combines both these features, showing that scale-free avalanches are the signature of a system posed near the spinodal line of a rst order transition, with many spatiotemporal patterns stored as dynamical metastable attractors. Specically, we studied a network of leaky integrate and re neurons, whose connections are the result of the learning of multiple spatiotemporal dynamical patterns, each with a randomly chosen ordering of the neurons. We found that the network shows a rst order transition between a low spiking rate disordered state (down), and a high rate state characterized by the emergence of collective activity and the replay of one of the stored patterns (up). The transition is characterized by hysteresis, or alternation of up and down states, depending on the lifetime of the metastable states. In both cases, critical features and neural avalanches are observed. Notably, critical phenomena occur at the edge of a discontinuous phase transition, as recently observed in a network of glow lamps

Criticality of neuronal avalanches in human sleep and their relationship with sleep macro- and micro-architecture

Sleep plays a key role in preserving brain function, keeping the brain network in a state that ensures optimal computational capabilities. Empirical evidence indicates that such a state is consistent with criticality, where scale-free neuronal avalanches emerge. However, the relationship between sleep, emergent avalanches, and criticality remains poorly understood. Here we fully characterize the critical behavior of avalanches during sleep, and study their relationship with the sleep macro- and micro-architecture, in particular the cyclic alternating pattern (CAP). We show that avalanche size and duration distributions exhibit robust power laws with exponents approximately equal to −3/2 e −2, respectively. Importantly, we find that sizes scale as a power law of the durations, and that all critical exponents for neuronal avalanches obey robust scaling relations, which are consistent with the mean-field directed percolation universality class. Our analysis demonstrates that avalanche dynamics depends on the position within the NREM-REM cycles, with the avalanche density increasing in the descending phases and decreasing in the ascending phases of sleep cycles. Moreover, we show that, within NREM sleep, avalanche occurrence correlates with CAP activation phases, particularly A1, which are the expression of slow wave sleep propensity and have been proposed to be beneficial for cognitive processes. The results suggest that neuronal avalanches, and thus tuning to criticality, actively contribute to sleep development and play a role in preserving network function. Such findings, alongside characterization of the universality class for avalanches, open new avenues to the investigation of functional role of criticality during sleep with potential clinical application.Significance statementWe fully characterize the critical behavior of neuronal avalanches during sleep, and show that avalanches follow precise scaling laws that are consistent with the mean-field directed percolation universality class. The analysis provides first evidence of a functional relationship between avalanche occurrence, slow-wave sleep dynamics, sleep stage transitions and occurrence of CAP phase A during NREM sleep. Because CAP is considered one of the major guardians of NREM sleep that allows the brain to dynamically react to external perturbation and contributes to the cognitive consolidation processes occurring in sleep, our observations suggest that neuronal avalanches at criticality are associated with flexible response to external inputs and to cognitive processes, a key assumption of the critical brain hypothesis

Assessment of a New Nanostructured Microemulsion System for Ocular Delivery of Sorafenib to Posterior Segment of the Eye

Eye drop formulations allowing topical treatment of retinal pathologies have long been sought as alternatives to intravitreal administration. This study aimed to assess whether a novel nanostructured microemulsions system (NaMESys) could be usefully employed to deliver sorafenib to the retina following topical instillation. NaMESys carrying 0.3% sorafenib (NaMESys-SOR) proved to be cytocompatible in vitro on rabbit corneal cells, and well-tolerated following b.i.d. ocular administration to rabbits during a 3-month study. In rats subject to retinal ischemia-reperfusion, NaMESys-SOR significantly inhibited retinal expression of tumor necrosis factor-alpha (TNFα, 20.7%) and inducible nitric oxide synthase (iNos, 87.3%) mRNAs in comparison to controls. Similarly, in streptozotocin-induced diabetic rats, NaMESys-SOR inhibited retinal expression of nuclear factor kappa B (NFκB), TNFα, insulin like growth factor 1 (IGF1), IGF1 receptor (IGF1R), vascular endothelial growth factor receptor 1 (VEGFR1) and 2 (VEGFR2) mRNAs by three-fold on average compared to controls. Furthermore, a reduction in TNFα, VEGFR1 and VEGFR2 protein expression was observed by western blot. Moreover, in mice subject to laser-induced choroidal neovascularization, NaMESys-SOR significantly inhibited neovascular lesions by 54%. In conclusion, NaMESys-SOR was shown to be a well-tolerated ophthalmic formulation able to deliver effective amounts of sorafenib to the retina, reducing proinflammatory and pro-angiogenic mediators in reliable models of proliferative retinopathies. These findings warrant further investigations on the full therapeutic potential of NaMESys-SOR eye drops, aiming to address unmet needs in the pharmacotherapy of retinal neovascular diseases